Results 261 to 270 of about 247,756 (301)

Fuzzy rules extraction, reasoning and rules adaptation in fuzzy neural networks

Proceedings of International Conference on Neural Networks (ICNN'97), 2002
This paper introduces a method for fuzzy rules extraction from a fuzzy neural network called FuNN. The process of reasoning in FuNN has been formalised and presented as a synergistic reasoning method. A bench-mark test data set of a chaotic time-series is used to illustrate the methods.
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Relational partitioning of fuzzy rules

Fuzzy Sets and Systems, 1996
Abstract We discuss the process of fuzzy systems model building and describe the role played by the partitioning of the input space. We also introduce and investigate the idea of using fuzzy relations in the antecedent parts of the rules and show how to reason with these types of rules.
Ronald R. Yager, Dimitar P. Filev
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Genetic fuzzy rules for DOPs

Proceedings of the 14th annual conference companion on Genetic and evolutionary computation, 2012
Dynamic Optimization Problems (DOPs) are a defiance for Genetic Algorithms. In DOPs, a varied number of optima, either local or global, that dynamically change their position and shape in the search space. When applied to DOPs, the standard Genetic Algorithms (SGAs) loose the population diversity.
Khalid Jebari, Abdelaziz Bouroumi, Aziz Ettouhami   +2 more
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Fuzzy Functional Dependencies and Fuzzy Association Rules

1999
This paper proposes fuzzy association rule which is a more generalized concept than boolean, quantitative, and interval association rules. Fuzzy association rule is a spectrum of definitions. Each particular fuzzy association rule can be defined by adding restrictions on the fuzziness depending on the needs of practical situations.
Yuping Yang, Mukesh Singhal
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Fuzzy sets, fuzzy clustering and fuzzy rules in AI

1994
We discuss the use of fuzzy set theory and semantic unification for fuzzy clustering and the use of fuzzy rules in knowlege bases. The paper provides a unification with probability theory and probabilistic fuzzy rules are discussed. Fuzzy sets are used to provide generalisation in clustering and pattern recognition methods.
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Logical structure of fuzzy IF-THEN rules

Fuzzy Sets and Systems, 2006
This paper discusses fuzzy IF-THEN rules in the framework of fuzzy type theory as developed by the first author in, e.g., [Fuzzy Sets Syst. 149, No. 2, 235--273 (2005; Zbl 1068.03019)]. The main aim is to treat such rules really as linguistic expressions and to model them as special cases within a broader formalization of natural language formulations.
Vilém Novák, Stephan Lehmke
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Fuzzy rules for HTML transcoding

Proceedings of the 35th Annual Hawaii International Conference on System Sciences, 2003
With the increasing availability of Web-enabled mobile devices, we are facing the problem of effectively adapting Web content for those devices. For adaptation, Web page structures require rearrangement, ie, transcoding, to better fit on small displays when layout-specific HTML structures like tables and frames are used.
Robbie Schaefer, Andreas Dangberg, Wolfgang Müller 0003   +2 more
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Mining fuzzy association rules

Proceedings of the sixth international conference on Information and knowledge management, 1997
In his paper, we introduce a novel technique, called F-APACS, for mining jkzy association rules. &istlng algorithms involve discretizing the domains of quantitative attrilmtes into intervals so as to discover quantitative association rules. i%ese intervals may not be concise and meaning@ enough for human experts to easily obtain nontrivial knowledge ...
Keith C. C. Chan, Wai-Ho Au
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FUZZY PATTERN RECOGNITION BY FUZZY INTEGRALS AND FUZZY RULES

2001
We give an overview of the application of fuzzy rules and fuzzy integrals in classification, presenting the general methodology and illustrating it by giving real applications. Fuzzy rules have been most of the time devoted to fuzzy control, using the so-called “Mamdani rules”. Here we present a broader view of the topic in the framework of possibility
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Weighted fuzzy production rules

Fuzzy Sets and Systems, 1997
Abstract Most of the research works on fuzzy production rules (FPRs) show that its knowledge representation power suffers from a serious shortcoming in that all propositions in the antecedent part are assumed to have equal importance (the lack of “local weight” concept), and that a number of rules executed in an inference path leading to a specified ...
Daniel S. Yeung, Eric C. C. Tsang
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